code: def _multiclass_recall_at_fixed_precision_arg_compute(
      state: Union[Tensor, Tuple[Tensor, Tensor]],
      num_classes: int,
      thresholds: Optional[Tensor],
      min_precision: float,
      reduce_fn: Callable = _recall_at_precision,
  ) -> Tuple[Tensor, Tensor]:
      (
          precision,
          recall,
          thresholds,
      ) = _multiclass_precision_recall_curve_compute(
          state, num_classes, thresholds
      )
      if isinstance(state, Tensor):
          res = [
              reduce_fn(p, r, thresholds, min_precision)
              for p, r in zip(precision, recall)
          ]
      else:
          res = [
              reduce_fn(p, r, t, min_precision)
              for p, r, t in zip(precision, recall, thresholds)
          ]
      recall = torch.stack([r[0] for r in res])
      thresholds = torch.stack([r[1] for r in res])
      return recall, thresholds
  
file_path: torchmetrics/src/torchmetrics/functional/classification/recall_fixed_precision.py
imports: from typing import Callable, List, Optional, Tuple, Union
  import torch
  from torch import Tensor
  from typing_extensions import Literal
  from torchmetrics.functional.classification.precision_recall_curve import _binary_precision_recall_curve_arg_validation, _binary_precision_recall_curve_compute, _binary_precision_recall_curve_format, _binary_precision_recall_curve_tensor_validation, _binary_precision_recall_curve_update, _multiclass_precision_recall_curve_arg_validation, _multiclass_precision_recall_curve_compute, _multiclass_precision_recall_curve_format, _multiclass_precision_recall_curve_tensor_validation, _multiclass_precision_recall_curve_update, _multilabel_precision_recall_curve_arg_validation, _multilabel_precision_recall_curve_compute, _multilabel_precision_recall_curve_format, _multilabel_precision_recall_curve_tensor_validation, _multilabel_precision_recall_curve_update
  from torchmetrics.utilities.enums import ClassificationTask
label_desc: Use image node_id 7 for calling a global function with example usage: _multiclass_recall_at_fixed_precision_arg_compute(state, num_classes, thresholds, min_precision, reduce_fn) and returns: recall,  thresholds